Part of the resting-state pipeline includes warping each individual anatomical image into a standardized space, so that results can be compared across subjects. This also means that we can place a seed voxel or seed region into one location of the brain, and it will be roughly in the same spot for every subject in our analysis.

To do this, we will focus on one of the core components of the so-called "resting-state network," which is a reliable pattern of connectivity observed when subjects are at rest. Several studies have revealed patterns of correlative activity between the ventromedial prefrontal cortex (vmPFC) and retrosplenial cortex, which is the network we will be focusing on for this tutorial series; our aim will be to compare correlations between these nodes across persons with autism and a control group without autism.

First, however, we will need to create and place the seed region appropriately. We can place a seed voxel in the vmPFC using the XYZ coordinates 0, -50, -5 (similar to MNI coordinates of 0, +50, -5), and a correlation coefficient will be estimated for every other voxel in the brain. The resulting correlation maps will be created for each subject, and then collapsed across groups and statistically compared against each other.

The procedure for generating an ROI is exactly the same as what was done in a previous post about 3dUndump; we simply put the coordinates into a text file, and tell 3dUndump how large a sphere we want to create around those coordinates.

This will then create a sphere with a 5mm radius around those coordinates, and information about that time series can then be extracted and correlated with other time series in every other voxel in the brain.